DESCRIPTION: This proposal aims to further our understanding of the relationship between the structure and composition of amino acid and peptides and their chemical properties using 1) hydrogen deuterium exchange (HDX), 2) infrared multiphoton dissociation spectroscopy (IRMPD), and 3) peptide fragmentation studies. The major goals of these studies are to enhance our understanding of the role of intramolecular hydrogen bonding on the structure and fragmentation pathways of peptides containing unusual amino acids. This information will then be integrated into searching algorithms for automated, mass spectrometry-based proteomics studies, and ultimately will create positive impacts for human health. Area 1 aims to study amino acid and peptide structure by determining rate coefficients for HDX and by measuring infrared spectra for these species in collaboration with Professor Steven Kass from the University of Minnesota. These projects are part of our on-going studies of the effects of intramolecular hydrogen bonding in the gas phase. The HDX studies will be carried out in a modified LCQ ion trap instrument. Undergraduates from William and Mary will travel to Minnesota for the summers to perform IRMPD and combined HDX-IRMPD experiments. In addition, detailed computational investigations of the mechanisms for HDX in the different AAs and peptides will be carried out in collaboration with Prof. Jennifer Poutsma's group at ODU. Area 2 aims to carry out the systematic study of fragmentation mechanisms of NPAA-containing peptides. These studies complement efforts to understand the effects of intramolecular hydrogen bonding on the gas-phase chemistry of amino acids and peptides. The ultimate goals are to further the understanding of a) the mechanisms for selective fragmentations in low-energy tandem mass spectrometry experiments that lead to incomplete sequence coverage for the peptide of interest and macrocylization, which leads to sequence scrambling, and b) to determine which specific NPAAs cause unusual fragmentation behavior when incorporated into peptides. This detailed knowledge can be integrated into peptide sequencing packages so that they can better account for these phenomena, which will ultimately lead to more robust searching algorithms.